Main Reference PaperBuilding an intrusion detection system using a filter-based feature selection algorithm, IEEE Transactions on Computers, 2016
  • In order to build the effective Intrusion Detection system (IDS), the proposed Flexible Mutual Information Feature Selection (FMIFS) algorithm intended to capture the optimal set of the feature through the supervised learning method referred as Least Square Support Vector Machine (LSSVM). It alleviates the issue of network traffic classification owing to the unnecessary features.

+ Description
  • In order to build the effective Intrusion Detection system (IDS), the proposed Flexible Mutual Information Feature Selection (FMIFS) algorithm intended to capture the optimal set of the feature through the supervised learning method referred as Least Square Support Vector Machine (LSSVM). It alleviates the issue of network traffic classification owing to the unnecessary features.

  • To extract the relevant features

  • To improve the accuracy

+ Aim & Objectives
  • To extract the relevant features

  • To improve the accuracy

  • The attention mechanism for the optimization of search strategy contributes to the enhanced performance of the system.

+ Contribution
  • The attention mechanism for the optimization of search strategy contributes to the enhanced performance of the system.

  • Operating system: Ubuntu / Windows

  • Java/Python/R

+ Software Tools & Technologies
  • Operating system: Ubuntu / Windows

  • Java/Python/R

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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